public class GIS extends AbstractEventTrainer
| Modifier and Type | Field and Description |
|---|---|
static String |
MAXENT_VALUE |
static boolean |
PRINT_MESSAGES
Set this to false if you don't want messages about the progress of model
training displayed.
|
static double |
SMOOTHING_OBSERVATION
If we are using smoothing, this is used as the "number" of times we want
the trainer to imagine that it saw a feature that it actually didn't see.
|
DATA_INDEXER_ONE_PASS_VALUE, DATA_INDEXER_PARAM, DATA_INDEXER_TWO_PASS_VALUEALGORITHM_PARAM, CUTOFF_DEFAULT, CUTOFF_PARAM, ITERATIONS_DEFAULT, ITERATIONS_PARAM, TRAINER_TYPE_PARAMEVENT_VALUE| Constructor and Description |
|---|
GIS() |
| Modifier and Type | Method and Description |
|---|---|
AbstractModel |
doTrain(DataIndexer indexer) |
boolean |
isSortAndMerge() |
boolean |
isValid() |
static GISModel |
trainModel(int iterations,
DataIndexer indexer)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
boolean smoothing)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
boolean printMessagesWhileTraining,
boolean smoothing,
Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
boolean printMessagesWhileTraining,
boolean smoothing,
Prior modelPrior,
int cutoff,
int threads)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm with the specified number of
iterations, data indexer, and prior.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
boolean smoothing)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
int iterations,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
int iterations,
int cutoff,
boolean smoothing,
boolean printMessagesWhileTraining)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
int iterations,
int cutoff,
double sigma)
Train a model using the GIS algorithm.
|
getDataIndexer, traingetAlgorithm, getCutoff, getIterations, initequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitinitpublic static final String MAXENT_VALUE
public static boolean PRINT_MESSAGES
public static double SMOOTHING_OBSERVATION
public boolean isValid()
isValid in class AbstractEventTrainerpublic boolean isSortAndMerge()
isSortAndMerge in class AbstractEventTrainerpublic AbstractModel doTrain(DataIndexer indexer) throws IOException
doTrain in class AbstractEventTrainerIOExceptionpublic static GISModel trainModel(ObjectStream<Event> eventStream) throws IOException
eventStream - The EventStream holding the data on which this model will be
trained.IOExceptionpublic static GISModel trainModel(ObjectStream<Event> eventStream, boolean smoothing) throws IOException
eventStream - The EventStream holding the data on which this model will be
trained.smoothing - Defines whether the created trainer will use smoothing while
training the model.IOExceptionpublic static GISModel trainModel(ObjectStream<Event> eventStream, int iterations, int cutoff) throws IOException
eventStream - The EventStream holding the data on which this model will be
trained.iterations - The number of GIS iterations to perform.cutoff - The number of times a feature must be seen in order to be relevant
for training.IOExceptionpublic static GISModel trainModel(ObjectStream<Event> eventStream, int iterations, int cutoff, boolean smoothing, boolean printMessagesWhileTraining) throws IOException
eventStream - The EventStream holding the data on which this model will be
trained.iterations - The number of GIS iterations to perform.cutoff - The number of times a feature must be seen in order to be relevant
for training.smoothing - Defines whether the created trainer will use smoothing while
training the model.printMessagesWhileTraining - Determines whether training status messages are written to STDOUT.IOExceptionpublic static GISModel trainModel(ObjectStream<Event> eventStream, int iterations, int cutoff, double sigma) throws IOException
eventStream - The EventStream holding the data on which this model will be
trained.iterations - The number of GIS iterations to perform.cutoff - The number of times a feature must be seen in order to be relevant
for training.sigma - The standard deviation for the gaussian smoother.IOExceptionpublic static GISModel trainModel(int iterations, DataIndexer indexer, boolean smoothing)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.smoothing - Defines whether the created trainer will use smoothing while
training the model.public static GISModel trainModel(int iterations, DataIndexer indexer)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.public static GISModel trainModel(int iterations, DataIndexer indexer, Prior modelPrior, int cutoff)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.modelPrior - The prior distribution for the model.public static GISModel trainModel(int iterations, DataIndexer indexer, boolean printMessagesWhileTraining, boolean smoothing, Prior modelPrior, int cutoff)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.printMessagesWhileTraining - Determines whether training status messages are written to STDOUT.smoothing - Defines whether the created trainer will use smoothing while
training the model.modelPrior - The prior distribution for the model.cutoff - The number of times a predicate must occur to be used in a model.public static GISModel trainModel(int iterations, DataIndexer indexer, boolean printMessagesWhileTraining, boolean smoothing, Prior modelPrior, int cutoff, int threads)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.printMessagesWhileTraining - Determines whether training status messages are written to STDOUT.smoothing - Defines whether the created trainer will use smoothing while
training the model.modelPrior - The prior distribution for the model.cutoff - The number of times a predicate must occur to be used in a model.Copyright © 2015 The Apache Software Foundation. All rights reserved.